Related Experiment Video
Updated: Mar 21, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Nonlinear Relationship between Birth Weight and Visceral Fat in Adolescents
Brian K Stansfield1, Mary Ellen Fain2, Jatinder Bhatia3
1Division of Neonatology, Department of Pediatrics, Medical College of Georgia, Augusta University, Augusta, GA; Vascular Biology Center, Augusta University, Augusta, GA.
Objective:
To determine the association of birth weight with abdominal fat distribution and markers known to increase risk for cardiovascular disease and type 2 diabetes in adolescents.
Study Design:
In 575 adolescents aged 14-18 years (52% female, 46% black), birth weight was obtained by parental recall. Fasting blood samples were measured for glucose, insulin, lipids, adiponectin, leptin, and C-reactive protein. Subcutaneous abdominal adipose tissue and visceral adipose tissue were assessed by magnetic resonance imaging.
Results:
When we compared markers of cardiometabolic risk across tertiles of birth weight, adjusting for age, sex, race, Tanner stage, physical activity, socioeconomic status, and body mass index, there were significant U-shaped trends for homeostasis model assessment of insulin resistance, leptin, and visceral adipose tissue (all Pquadratic < .05). A significant linear downward trend across tertiles of birth weight was observed for triglycerides (Plinear = .03). There were no differences in fasting glucose, blood pressure, total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, adiponectin, C-reactive protein, or subcutaneous abdominal adipose tissue across tertiles of birth weight.
Conclusions:
Our data suggest that both low and high birth weights are associated with greater visceral adiposity and biomarkers implicated in insulin resistance and inflammation in adolescents.
Related Concept Videos
Cholesterol: Significance and Regulation
Considering cholesterol and...
Signs of Puberty
Obesity
Hypodermis
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...

